Method for supporting the operation of a vehicle with a sensor unit, computer program product and system

Abstract

The invention relates to a method (100) for supporting the operation of a vehicle (2) with a sensor unit (4) for acquiring sensor data (200) for an evaluation in a trained, artificial neural network (10) with a plurality of network elements (11) for intermediate evaluations (210) of the sensor data (200), the method comprising the following steps: providing (102) the sensor data (200) for the neural network (10), evaluating (103) the sensor data (200) by means of the neural network (10) in view of a result. The invention also relates to a computer program product and to a system (1).

1 . A method ( 100 ) for supporting the operation of a vehicle ( 2 ) with a sensor unit ( 4 ) for acquiring sensor data ( 200 ) for analysis in a trained, artificial neural network ( 10 ) comprising a plurality of network elements ( 11 ) for interim analyses ( 210 ) of the sensor data ( 200 ), comprising the following steps:
 Providing ( 102 ) the sensor data ( 200 ) for the neural network ( 10 ),   Analyzing ( 103 ) the sensor data ( 200 ) for detecting at least one event by the neural network ( 10 ),   Monitoring ( 104 ) an analysis behavior of the interim analyses ( 210 ) when analyzing ( 103 ) the sensor data ( 200 ),   Evaluating ( 105 ) the sensor data ( 200 ) for detecting a sensor interference as a function of the analysis behavior,   Carrying out a reaction measure ( 106 ) as a function of evaluating ( 105 ) the sensor data ( 200 ).   
     
     
         2 . The method ( 100 ) according to  any of the preceding claims , characterized in that the network elements ( 11 ) comprise network layers, network filters and/or weightings of the neural network ( 10 ). 
     
     
         3 . The method ( 100 ) according to  any of the preceding claims , characterized in that the method ( 100 ) comprises the following step:
 identifying ( 101 ) key elements ( 11 . 1 ) of the plurality of network elements ( 11 ), wherein, when monitoring ( 104 ) the analysis behavior, the interim analyses ( 210 ) of the key elements ( 11 . 1 ) are monitored.   
     
     
         4 . The method ( 100 ) according to  any of the preceding claims , characterized in that, for identifying ( 101 ) the key elements ( 11 . 1 ) and/or for evaluating ( 105 ) the sensor data ( 200 ), a calibration process ( 101 . 1 ) is executed, in which interference-affected reference data ( 201 ) and interference-free reference data ( 202 ) are analyzed by the neural network ( 10 ), wherein behavioral deviations of the interim analyses ( 210 ) are detected during the calibration process ( 101 . 1 ) when analyzing ( 103 ) the interference-affected and interference-free reference data ( 201 ,  202 ). 
     
     
         5 . The method ( 100 ) according to  any of the preceding claims , characterized in that the calibration process ( 101 . 1 ) is executed by a server ( 5 ), wherein analyzing ( 103 ) the sensor data ( 200 ), monitoring ( 104 ) the analysis behavior and evaluating ( 105 ) the sensor data ( 200 ) is carried out by the vehicle ( 2 ). 
     
     
         6 . The method ( 100 ) according to  any of the preceding claims , characterized in that the key elements ( 11 . 1 ) are weighted when identifying ( 101 ) the key elements ( 11 . 1 ), wherein the weighting is taken into account when evaluating ( 105 ) the sensor data ( 200 ). 
     
     
         7 . The method ( 100 ) according to  any of the preceding claims , characterized in that an averaging for several interim analyses ( 210 ) is performed when evaluating ( 105 ) the sensor data ( 200 ) and/or when monitoring ( 104 ) an analysis behavior of the interim analyses ( 210 ). 
     
     
         8 . The method ( 100 ) according to  any of the preceding claims , characterized in that a comparison of the analysis behavior with a reference behavior of the interim analyses ( 210 ) is performed when evaluating ( 105 ) the sensor data ( 200 ), wherein at least one limit value ( 212 ) for a deviation of the analysis behavior from the reference behavior for detecting the sensor interference is specified for the evaluation of the sensor data ( 200 ). 
     
     
         9 . The method ( 100 ) according to  any of the preceding claims , characterized in that the sensor data ( 200 ) are classified with regard to an interference classification ( 213 ) when evaluating ( 105 ) the sensor data ( 200 ), wherein the reaction measure ( 106 ) is carried out as a function of the interference classification ( 213 ). 
     
     
         10 . The method ( 100 ) according to  any of the preceding claims , characterized in that the reaction measure ( 106 ) comprises a validation process ( 106 . 1 ) for validating the evaluation and/or the analysis of the sensor data ( 200 ). 
     
     
         11 . The method ( 100 ) according to  any of the preceding claims , characterized in that the validation process ( 106 . 1 ) comprises loading the sensor data ( 200 ) into a further, artificial neural network ( 10 . 1 ) which is trained for analyzing ( 103 ) sensor data ( 200 ) of the interference classification ( 213 ) for detecting the event. 
     
     
         12 . The method ( 100 ) according to  any of the preceding claims , characterized in that the validation process ( 106 . 1 ) comprises loading the sensor data ( 200 ) into several further, trained artificial neural networks ( 10 . 2 ), wherein a consolidation process is executed to obtain an overall evaluation of the sensor data ( 200 ) with regard to the event and/or with regard to the sensor interference. 
     
     
         13 . The method ( 100 ) according to  any of the preceding claims , characterized in that the reaction measure ( 106 ) comprises an automatic triggering of a driving maneuver of the vehicle ( 2 ). 
     
     
         14 . A computer program product, comprising commands which, when executed by the computing unit ( 3 ), cause the computing unit ( 3 ) to execute the method ( 100 ) according to  any of the preceding claims . 
     
     
         15 . A system ( 1 ), comprising a vehicle ( 2 ) comprising a sensor unit ( 4 ) for acquiring sensor data ( 200 ) and a computing unit ( 3 ) for executing a method ( 100 ) according to  any of the preceding claims .